Gastroenterology

Machine learning-based model for identifying liver injury in patients with thyroid-associated ophthalmopathy.

PURPOSE: To explore the relationship between thyroid-associated ophthalmopathy (TAO) and liver injury and establish a model for identifying liver injury by using machine learning so as to provide an effective diagnostic tool for liver injury in patients with TAO. METHOD: A single-center retrospective study was conducted to collect the clinical data of 318 patients with TAO admitted to a hospital f...

An efficient framework for real-time colorectal polyp detection using local outlier factor-based preprocessing and YOLOv11n.

Timely and accurate detection of colorectal polyps plays an important role in the prevention and early diagnosis of colorectal cancer. Despite the advancement of deep learning-based methods, automatic polyp detection remains a challenging problem due to factors such as the small size of polyps, apparent similarity of polyps to surrounding tissue, variable quality of colonoscopy images, and the pre...

Screening of core targets for Di(2-ethylhexyl) Phthalate-related gastric cancer based on machine learning, molecular docking, and SHAP analysis.

PURPOSE: Given the existing uncertainties regarding the link between Di(2-ethylhexyl) phthalate (DEHP) exposure and gastric cancer (GC) progression, t...

Deep Learning Predicts Imminent Tumor Progression in Advanced Pancreatic Adenocarcinoma Using Serial CT Scans During Chemotherapy.

Advanced pancreatic ductal adenocarcinoma (PDAC) often progresses rapidly during chemotherapy despite initial assessments of stable disease or partial...

Multistage microrobots with pH-responsive release of platelet membrane-coated nanoparticles.

Targeted drug delivery in the gastrointestinal tract remains challenging because therapeutics must overcome multiple hierarchical barriers before reac...

Acute Aluminum Phosphide Poisoning: Evolving Perspectives on Toxic Mechanisms and Evidence-Based Clinical Management.

Aluminum phosphide (AlP) is a chemical compound that is used as a pesticide for suicidal purposes and can cause death, and it poses a challenge to hea...

A prospective development and evaluation of a 2D convolutional neural network-based auto-segmentation model for cervical cancer radiotherapy.

BACKGROUND: Accurate delineation of target volumes and organs at risk (OAR) is essential in radiotherapy planning for cervical cancer. Deep learning (...

A modern review of uveal melanoma: molecular insights, clinical management, and emerging therapies.

Uveal melanoma is the most frequent primary intraocular malignancy in adults and is characterized by an aggressive clinical course, high propensity fo...

CMTM3 links inflammation-related transcriptional dysregulation to immune and therapeutic stratification in gastric cancer.

Gastric cancer (GC) shows strong biological heterogeneity and frequent disruption of inflammatory and metabolic programs, which affect tumor progressi...

Artificial Intelligence-Enabled Opportunities to Reduce Administrative Bloat in Gastroenterology Practices: Scoping Review.

BACKGROUND AND AIMS: Healthcare administration accounts for approximately 25% of healthcare expenditures. We performed a scoping review of AI-enabled ...

Precision-Driven Management of Great Saphenous Varicose Veins: A Narrative Review.

OBJECTIVES: Great saphenous vein (GSV) incompetence is common, but numerous treatment options complicate patient-treatment matching. This narrative re...

Decoding the Partitioning Behavior of Poly- and Perfluoroalkyl Substances: Insights from Human Liver and Blood Biomonitoring with Machine Learning.

Perfluoroalkyl substances (PFASs) are known for their tendency to accumulate in the human liver, potentially causing hepatotoxic effects. However, the...

IgA-Enriched Phenotype Predicts Liver-Related Events in MASLD.

BACKGROUND & AIMS: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a complex, multifactorial condition. To achieve truly personali...

Automated MRI Liver Segmentation For Accurate Quantification Of Hepatic Steatosis.

RATIONALE AND OBJECTIVES: MRI-proton density fat fraction (MRI-PDFF) is widely applied in clinical practice for hepatic fat quantification. However, t...

Single-Cell and Bulk RNA Sequencing Reveal MCL1 as a Key Regulator of Mitochondrial Function in Liver Ischemia-Reperfusion Injury.

Liver ischemia-reperfusion injury (LIRI), a significant complication following liver transplantation and surgical procedures, remains inadequately add...

Multi-Omics Framework Integrating Genetics, Microbiome, Metabolism, and Immunity for Deciphering Ulcerative Colitis Pathogenesis and Diagnostic Biomarker Discovery.

Ulcerative colitis (UC) is an inflammatory bowel disease involving complex interactions between genetics, gut microbiota, metabolism, and immunity. Th...

From Symptom Control to Precision Supportive Oncology: Integrating Artificial Intelligence in Supportive Oncology for Gastrointestinal Cancers.

PURPOSE OF REVIEW: Gastrointestinal (GI) cancers are among the most common malignancies worldwide and impose a substantial symptom burden from diagnos...

Gut microbiome in pediatric acute pancreatitis and Crohn's disease versus irritable bowel syndrome and healthy controls.

OBJECTIVES: Pediatric acute pancreatitis (AP), Crohn's disease (CD), and irritable bowel syndrome (IBS) are associated with gut dysbiosis, but differe...

Automated model-based lesion tracking in CT: colorectal liver metastases as a use case for development and performance analysis.

OBJECTIVE: To develop and evaluate an automated CT liver lesion-tracking algorithm that matches lesions over time, detects new metastases, and reports...

Use of an AI Image Recognition-Based Smartphone App in Personalized Bowel Preparation Before Colonoscopy: Prospective Randomized Controlled Trial.

BACKGROUND: Sufficient bowel preparation is critical for increasing the quality of colonoscopy. However, current bowel preparation guidelines have lim...